1. Field of the Invention
The present invention relates to a distributed water flow predicting device for predicting a distributed water flow rate from a purification plant of a water-supply facility or a service reservoir, especially a distributed water flow predicting device using a neural network model.
2. Related Background Art
In a water supply system, raw water is taken in from a dam-type reservoir in a mountain or a river and is led in a conduit to a purification plant. It takes a long period of time to lead the raw water from the intake plant to the purification plant. In principle flocculation, sedimentation or filtration of a purification process in the purification plant, cause a large time delay. Accordingly it is difficult to work the process from the intake to the distribution on feedback control in accordance with water demand changes. Thus it is necessary to predict a water demand for a day and make a water operational plan from intake at the water-supply plant to water distribution.
Water demand flow change in accordance with 1) seasons, 2) meteorological conditions, such as weathers, temperatures, etc., 3) social life conditions, such as days of the week, special days, holidays, May holidays, New Year holidays, etc.
Thus to make a water operational plan from intake at a water-supply plant to distribution, a prediction model is identified statistically by actual distributed water flow data and it predicts a distributed water flow rate hourly one after another.
But the conventional method so-called sequential prediction method cannot make a daily water operational plan. Because the conventional method does not have learning ability based on actual data which are obtained every day as instruction signals, past distributed water flow data cannot be effectively used, and accordingly seasonal water demand changes and long-span structural changes due to population changes, piping works, etc. cannot be followed. Consequently daily operations rely on experts or plant operators.
An object of the present invention is to solve the above-described problems, and to provide a water demand predicting device which has ability of learning actual distributed water flow data and can predict a daily distributed water flow and hourly distributed water flow throughout a day for each season.